Pandas Profiling Report

Dataset statistics

Number of variables	22
Number of observations	15532
Missing cells	7364
Missing cells (%)	2.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	2.6 MiB
Average record size in memory	176.0 B

Variable types

Numeric	10
Categorical	12

Alerts

`ClaimInd` has constant value "1"	Constant
`RecordBeg` has a high cardinality: 349 distinct values	High cardinality
`RecordEnd` has a high cardinality: 360 distinct values	High cardinality
`df_index` is highly correlated with `Dataset`	High correlation
`LicAge` is highly correlated with `DrivAge` and 1 other fields	High correlation
`DrivAge` is highly correlated with `LicAge` and 1 other fields	High correlation
`BonusMalus` is highly correlated with `LicAge` and 1 other fields	High correlation
`Dataset` is highly correlated with `df_index`	High correlation
`df_index` is highly correlated with `Dataset`	High correlation
`LicAge` is highly correlated with `DrivAge` and 1 other fields	High correlation
`DrivAge` is highly correlated with `LicAge` and 1 other fields	High correlation
`BonusMalus` is highly correlated with `LicAge` and 1 other fields	High correlation
`Dataset` is highly correlated with `df_index`	High correlation
`df_index` is highly correlated with `Dataset`	High correlation
`LicAge` is highly correlated with `DrivAge` and 1 other fields	High correlation
`DrivAge` is highly correlated with `LicAge`	High correlation
`BonusMalus` is highly correlated with `LicAge`	High correlation
`Dataset` is highly correlated with `df_index`	High correlation
`Gender` is highly correlated with `ClaimInd`	High correlation
`ClaimNbFireTheft` is highly correlated with `ClaimInd`	High correlation
`SocioCateg` is highly correlated with `ClaimInd`	High correlation
`Dataset` is highly correlated with `ClaimInd`	High correlation
`ClaimNbParking` is highly correlated with `ClaimInd`	High correlation
`ClaimNbResp` is highly correlated with `ClaimInd`	High correlation
`HasKmLimit` is highly correlated with `ClaimInd`	High correlation
`MariStat` is highly correlated with `ClaimInd`	High correlation
`VehUsage` is highly correlated with `ClaimInd`	High correlation
`ClaimInd` is highly correlated with `Gender` and 8 other fields	High correlation
`df_index` is highly correlated with `Dataset`	High correlation
`LicAge` is highly correlated with `MariStat` and 3 other fields	High correlation
`MariStat` is highly correlated with `LicAge` and 1 other fields	High correlation
`SocioCateg` is highly correlated with `LicAge` and 2 other fields	High correlation
`VehUsage` is highly correlated with `SocioCateg` and 1 other fields	High correlation
`DrivAge` is highly correlated with `LicAge` and 4 other fields	High correlation
`BonusMalus` is highly correlated with `LicAge` and 2 other fields	High correlation
`Dataset` is highly correlated with `df_index`	High correlation
`ClaimNbResp` is highly correlated with `BonusMalus`	High correlation
`RecordEnd` has 7364 (47.4%) missing values	Missing
`ClaimAmount` is highly skewed (γ1 = 62.22157794)	Skewed
`df_index` has unique values	Unique
`LicAge` has 406 (2.6%) zeros	Zeros
`ClaimNbNonResp` has 10762 (69.3%) zeros	Zeros
`ClaimNbWindscreen` has 10238 (65.9%) zeros	Zeros
`OutUseNb` has 12547 (80.8%) zeros	Zeros

Reproduction

Analysis started	2021-11-15 17:01:13.122275
Analysis finished	2021-11-15 17:01:58.967834
Duration	45.85 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	15532
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	226187.6985

Minimum	145813
Maximum	310976
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	145813
5-th percentile	153949.5
Q1	186848
median	225879.5
Q3	265452.25
95-th percentile	300420.9
Maximum	310976
Range	165163
Interquartile range (IQR)	78604.25

Descriptive statistics

Standard deviation	46312.61788
Coefficient of variation (CV)	0.2047530356
Kurtosis	-1.145728219
Mean	226187.6985
Median Absolute Deviation (MAD)	39321.5
Skewness	0.03950834991
Sum	3513147333
Variance	2144858574
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
145813	1	< 0.1%
251973	1	< 0.1%
251643	1	< 0.1%
251648	1	< 0.1%
251650	1	< 0.1%
251673	1	< 0.1%
251694	1	< 0.1%
251725	1	< 0.1%
251730	1	< 0.1%
251744	1	< 0.1%
Other values (15522)	15522	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
145813	1	< 0.1%
145814	1	< 0.1%
145833	1	< 0.1%
145845	1	< 0.1%
145846	1	< 0.1%
145850	1	< 0.1%
145863	1	< 0.1%
145866	1	< 0.1%
145883	1	< 0.1%
145899	1	< 0.1%

Value	Count	Frequency (%)
310976	1	< 0.1%
310973	1	< 0.1%
310967	1	< 0.1%
310963	1	< 0.1%
310910	1	< 0.1%
310899	1	< 0.1%
310884	1	< 0.1%
310880	1	< 0.1%
310878	1	< 0.1%
310862	1	< 0.1%

Exposure
Real number (ℝ_≥0)

Distinct	739
Distinct (%)	4.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.5966357842

Minimum	0.002
Maximum	1
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	0.002
5-th percentile	0.143
Q1	0.408
median	0.606
Q3	0.833
95-th percentile	1
Maximum	1
Range	0.998
Interquartile range (IQR)	0.425

Descriptive statistics

Standard deviation	0.2638269567
Coefficient of variation (CV)	0.442190971
Kurtosis	-0.9637876155
Mean	0.5966357842
Median Absolute Deviation (MAD)	0.213
Skewness	-0.2398052898
Sum	9266.947
Variance	0.0696046631
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1046	6.7%
0.833	843	5.4%
0.916	810	5.2%
0.666	648	4.2%
0.749	638	4.1%
0.583	556	3.6%
0.5	481	3.1%
0.416	468	3.0%
0.75	458	2.9%
0.499	439	2.8%
Other values (729)	9145	58.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.002	5	< 0.1%
0.005	3	< 0.1%
0.008	7	< 0.1%
0.009	1	< 0.1%
0.01	4	< 0.1%
0.013	3	< 0.1%
0.014	2	< 0.1%
0.016	3	< 0.1%
0.019	5	< 0.1%
0.021	8	0.1%

Value	Count	Frequency (%)
1	1046	6.7%
0.998	16	0.1%
0.997	12	0.1%
0.996	17	0.1%
0.994	6	< 0.1%
0.993	4	< 0.1%
0.991	6	< 0.1%
0.99	11	0.1%
0.989	8	0.1%
0.987	12	0.1%

LicAge
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	18
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.401300541

Minimum	0
Maximum	17
Zeros	406
Zeros (%)	2.6%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	3
median	5
Q3	8
95-th percentile	11
Maximum	17
Range	17
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.046795481
Coefficient of variation (CV)	0.5640855305
Kurtosis	-0.6134681806
Mean	5.401300541
Median Absolute Deviation (MAD)	2
Skewness	0.2667288125
Sum	83893
Variance	9.282962702
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=18)

Value	Count	Frequency (%)
5	1820	11.7%
2	1642	10.6%
8	1632	10.5%
4	1608	10.4%
3	1548	10.0%
7	1547	10.0%
6	1536	9.9%
1	1215	7.8%
9	1047	6.7%
10	724	4.7%
Other values (8)	1213	7.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	406	2.6%
1	1215	7.8%
2	1642	10.6%
3	1548	10.0%
4	1608	10.4%
5	1820	11.7%
6	1536	9.9%
7	1547	10.0%
8	1632	10.5%
9	1047	6.7%

Value	Count	Frequency (%)
17	1	< 0.1%
16	4	< 0.1%
15	18	0.1%
14	34	0.2%
13	80	0.5%
12	217	1.4%
11	453	2.9%
10	724	4.7%
9	1047	6.7%
8	1632	10.5%

RecordBeg
Categorical

HIGH CARDINALITY

Distinct	349
Distinct (%)	2.2%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

2004-01-01	6854
2004-04-01	837
2004-03-01	608
2004-02-01	548
2004-07-01	516
Other values (344)	6169

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	18 ?
Unique (%)	0.1%

Sample

1st row	2004-05-19
2nd row	2004-01-01
3rd row	2004-10-23
4th row	2004-01-01
5th row	2004-01-01

Common Values

Value	Count	Frequency (%)
2004-01-01	6854	44.1%
2004-04-01	837	5.4%
2004-03-01	608	3.9%
2004-02-01	548	3.5%
2004-07-01	516	3.3%
2004-06-01	458	2.9%
2004-05-01	423	2.7%
2004-09-01	261	1.7%
2004-10-01	242	1.6%
2004-08-01	219	1.4%
Other values (339)	4566	29.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2004-01-01	6854	44.1%
2004-04-01	837	5.4%
2004-03-01	608	3.9%
2004-02-01	548	3.5%
2004-07-01	516	3.3%
2004-06-01	458	2.9%
2004-05-01	423	2.7%
2004-09-01	261	1.7%
2004-10-01	242	1.6%
2004-08-01	219	1.4%
Other values (339)	4566	29.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

RecordEnd
Categorical

HIGH CARDINALITY
MISSING

Distinct	360
Distinct (%)	4.4%
Missing	7364
Missing (%)	47.4%
Memory size	121.5 KiB

2004-12-01	587
2004-10-01	566
2004-07-01	522
2004-11-01	479
2004-09-01	397
Other values (355)	5617

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	8 ?
Unique (%)	0.1%

Sample

1st row	2004-10-05
2nd row	2004-11-01
3rd row	2004-11-01
4th row	2004-12-16
5th row	2004-06-25

Common Values

Value	Count	Frequency (%)
2004-12-01	587	3.8%
2004-10-01	566	3.6%
2004-07-01	522	3.4%
2004-11-01	479	3.1%
2004-09-01	397	2.6%
2004-06-01	285	1.8%
2004-04-01	250	1.6%
2004-08-01	233	1.5%
2004-05-01	205	1.3%
2004-03-01	115	0.7%
Other values (350)	4529	29.2%
(Missing)	7364	47.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2004-12-01	587	7.2%
2004-10-01	566	6.9%
2004-07-01	522	6.4%
2004-11-01	479	5.9%
2004-09-01	397	4.9%
2004-06-01	285	3.5%
2004-04-01	250	3.1%
2004-08-01	233	2.9%
2004-05-01	205	2.5%
2004-03-01	115	1.4%
Other values (350)	4529	55.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Gender
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

0	9625
1	5907

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	9625	62.0%
1	5907	38.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9625	62.0%
1	5907	38.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

MariStat
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

0	12994
1	2538

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	12994	83.7%
1	2538	16.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	12994	83.7%
1	2538	16.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

SocioCateg
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

CSP5	10450
CSP6	2780
CSP4	1271
CSP2	443
CSP1	428
Other values (2)	160

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	CSP6
2nd row	CSP5
3rd row	CSP5
4th row	CSP6
5th row	CSP5

Common Values

Value	Count	Frequency (%)
CSP5	10450	67.3%
CSP6	2780	17.9%
CSP4	1271	8.2%
CSP2	443	2.9%
CSP1	428	2.8%
CSP3	159	1.0%
CSP7	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
csp5	10450	67.3%
csp6	2780	17.9%
csp4	1271	8.2%
csp2	443	2.9%
csp1	428	2.8%
csp3	159	1.0%
csp7	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

VehUsage
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

Private+trip to office	8421
Private	4264
Professional	2438
Professional run	409

Length

Max length	22
Median length	22
Mean length	16.15439093
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Private
2nd row	Private+trip to office
3rd row	Private+trip to office
4th row	Private
5th row	Private+trip to office

Common Values

Value	Count	Frequency (%)
Private+trip to office	8421	54.2%
Private	4264	27.5%
Professional	2438	15.7%
Professional run	409	2.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
private+trip	8421	25.7%
to	8421	25.7%
office	8421	25.7%
private	4264	13.0%
professional	2847	8.7%
run	409	1.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

DrivAge
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	56
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	46.87574041

Minimum	20
Maximum	75
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	20
5-th percentile	25
Q1	35
median	46
Q3	57
95-th percentile	73
Maximum	75
Range	55
Interquartile range (IQR)	22

Descriptive statistics

Standard deviation	14.25982527
Coefficient of variation (CV)	0.3042048007
Kurtosis	-0.895597215
Mean	46.87574041
Median Absolute Deviation (MAD)	11
Skewness	0.184724032
Sum	728074
Variance	203.3426166
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
75	594	3.8%
54	420	2.7%
56	410	2.6%
51	389	2.5%
55	373	2.4%
57	371	2.4%
38	371	2.4%
53	370	2.4%
41	365	2.3%
40	361	2.3%
Other values (46)	11508	74.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
20	35	0.2%
21	74	0.5%
22	131	0.8%
23	156	1.0%
24	179	1.2%
25	224	1.4%
26	265	1.7%
27	296	1.9%
28	280	1.8%
29	352	2.3%

Value	Count	Frequency (%)
75	594	3.8%
74	105	0.7%
73	118	0.8%
72	103	0.7%
71	125	0.8%
70	126	0.8%
69	129	0.8%
68	182	1.2%
67	157	1.0%
66	175	1.1%

HasKmLimit
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

0	14411
1	1121

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	14411	92.8%
1	1121	7.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	14411	92.8%
1	1121	7.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

BonusMalus
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	77
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	61.27105331

Minimum	50
Maximum	183
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	50
5-th percentile	50
Q1	50
median	50
Q3	71
95-th percentile	95
Maximum	183
Range	133
Interquartile range (IQR)	21

Descriptive statistics

Standard deviation	16.75145044
Coefficient of variation (CV)	0.2733990936
Kurtosis	3.116495996
Mean	61.27105331
Median Absolute Deviation (MAD)	0
Skewness	1.693147958
Sum	951662
Variance	280.6110917
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50	8219	52.9%
80	624	4.0%
90	589	3.8%
76	533	3.4%
85	522	3.4%
72	499	3.2%
68	441	2.8%
57	403	2.6%
64	395	2.5%
60	394	2.5%
Other values (67)	2913	18.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
50	8219	52.9%
51	270	1.7%
52	117	0.8%
53	87	0.6%
54	333	2.1%
55	152	1.0%
56	84	0.5%
57	403	2.6%
58	153	1.0%
59	75	0.5%

Value	Count	Frequency (%)
183	1	< 0.1%
175	1	< 0.1%
165	1	< 0.1%
156	7	< 0.1%
148	9	0.1%
147	13	0.1%
146	2	< 0.1%
143	2	< 0.1%
140	11	0.1%
139	5	< 0.1%

ClaimAmount
Real number (ℝ_≥0)

SKEWED

Distinct	8624
Distinct (%)	55.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2129.25981

Minimum	0.1885196375
Maximum	802620.271
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	0.1885196375
5-th percentile	93.97173716
Q1	323.3730363
median	781.1782477
Q3	2163.26284
95-th percentile	6914.46435
Maximum	802620.271
Range	802620.0825
Interquartile range (IQR)	1839.889804

Descriptive statistics

Standard deviation	10287.30525
Coefficient of variation (CV)	4.831399719
Kurtosis	4738.381136
Mean	2129.25981
Median Absolute Deviation (MAD)	637.4320242
Skewness	62.22157794
Sum	33071663.37
Variance	105828649.3
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1418.610272	603	3.9%
102.5900302	466	3.0%
4326.52568	280	1.8%
97.32326284	197	1.3%
1562.356495	190	1.2%
2764.169184	97	0.6%
2163.26284	90	0.6%
4241.691843	74	0.5%
1531.722054	50	0.3%
1093.413897	43	0.3%
Other values (8614)	13442	86.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.1885196375	1	< 0.1%
0.2356495468	1	< 0.1%
1.178247734	6	< 0.1%
1.767371601	1	< 0.1%
4.123867069	1	< 0.1%
4.783685801	2	< 0.1%
4.913293051	1	< 0.1%
6.315407855	1	< 0.1%
8.283081571	1	< 0.1%
8.836858006	2	< 0.1%

Value	Count	Frequency (%)
802620.271	2	< 0.1%
163427.0139	1	< 0.1%
154957.1801	2	< 0.1%
139031.3946	2	< 0.1%
119887.9795	2	< 0.1%
95150.96284	2	< 0.1%
84434.81148	1	< 0.1%
58086.52931	2	< 0.1%
55699.82356	2	< 0.1%
52976.59849	1	< 0.1%

ClaimInd
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

1	15532

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	15532	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	15532	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Dataset
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

6	4214
7	3639
8	3219
5	2418
9	2042

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	5
2nd row	5
3rd row	5
4th row	5
5th row	5

Common Values

Value	Count	Frequency (%)
6	4214	27.1%
7	3639	23.4%
8	3219	20.7%
5	2418	15.6%
9	2042	13.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
6	4214	27.1%
7	3639	23.4%
8	3219	20.7%
5	2418	15.6%
9	2042	13.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ClaimNbResp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

0.0	11619
1.0	3269
2.0	571
3.0	63
4.0	10

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	11619	74.8%
1.0	3269	21.0%
2.0	571	3.7%
3.0	63	0.4%
4.0	10	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	11619	74.8%
1.0	3269	21.0%
2.0	571	3.7%
3.0	63	0.4%
4.0	10	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ClaimNbNonResp
Real number (ℝ_≥0)

ZEROS

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3819855782

Minimum	0
Maximum	7
Zeros	10762
Zeros (%)	69.3%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	2
Maximum	7
Range	7
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.6458676619
Coefficient of variation (CV)	1.690816876
Kurtosis	4.579587282
Mean	0.3819855782
Median Absolute Deviation (MAD)	0
Skewness	1.890375626
Sum	5933
Variance	0.4171450367
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	10762	69.3%
1	3803	24.5%
2	807	5.2%
3	132	0.8%
4	22	0.1%
5	5	< 0.1%
7	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	10762	69.3%
1	3803	24.5%
2	807	5.2%
3	132	0.8%
4	22	0.1%
5	5	< 0.1%
7	1	< 0.1%

Value	Count	Frequency (%)
7	1	< 0.1%
5	5	< 0.1%
4	22	0.1%
3	132	0.8%
2	807	5.2%
1	3803	24.5%
0	10762	69.3%

ClaimNbParking
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

0.0	14191
1.0	1218
2.0	115
3.0	8

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	14191	91.4%
1.0	1218	7.8%
2.0	115	0.7%
3.0	8	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	14191	91.4%
1.0	1218	7.8%
2.0	115	0.7%
3.0	8	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ClaimNbFireTheft
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	121.5 KiB

0.0	14296
1.0	1145
2.0	90
4.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	14296	92.0%
1.0	1145	7.4%
2.0	90	0.6%
4.0	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	14296	92.0%
1.0	1145	7.4%
2.0	90	0.6%
4.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ClaimNbWindscreen
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4363893896

Minimum	0
Maximum	5
Zeros	10238
Zeros (%)	65.9%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	2
Maximum	5
Range	5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.6911115883
Coefficient of variation (CV)	1.583703923
Kurtosis	3.384159201
Mean	0.4363893896
Median Absolute Deviation (MAD)	0
Skewness	1.720527933
Sum	6778
Variance	0.4776352274
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	10238	65.9%
1	4071	26.2%
2	1010	6.5%
3	171	1.1%
4	36	0.2%
5	6	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	10238	65.9%
1	4071	26.2%
2	1010	6.5%
3	171	1.1%
4	36	0.2%
5	6	< 0.1%

Value	Count	Frequency (%)
5	6	< 0.1%
4	36	0.2%
3	171	1.1%
2	1010	6.5%
1	4071	26.2%
0	10238	65.9%

OutUseNb
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.3109708988

Minimum	0
Maximum	5
Zeros	12547
Zeros (%)	80.8%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2
Maximum	5
Range	5
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.7638578956
Coefficient of variation (CV)	2.456364562
Kurtosis	10.53932642
Mean	0.3109708988
Median Absolute Deviation (MAD)	0
Skewness	3.076759748
Sum	4830
Variance	0.5834788847
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	12547	80.8%
1	1869	12.0%
2	631	4.1%
3	290	1.9%
4	146	0.9%
5	49	0.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	12547	80.8%
1	1869	12.0%
2	631	4.1%
3	290	1.9%
4	146	0.9%
5	49	0.3%

Value	Count	Frequency (%)
5	49	0.3%
4	146	0.9%
3	290	1.9%
2	631	4.1%
1	1869	12.0%
0	12547	80.8%

RiskArea
Real number (ℝ_≥0)

Distinct	13
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.88301571

Minimum	1
Maximum	13
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	121.5 KiB

Quantile statistics

Minimum	1
5-th percentile	4
Q1	6
median	8
Q3	10
95-th percentile	11
Maximum	13
Range	12
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.239167609
Coefficient of variation (CV)	0.284049619
Kurtosis	-0.6169234101
Mean	7.88301571
Median Absolute Deviation (MAD)	2
Skewness	-0.3378824716
Sum	122439
Variance	5.013871582
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
7	3343	21.5%
10	2909	18.7%
6	2164	13.9%
9	2143	13.8%
11	1953	12.6%
5	1033	6.7%
8	838	5.4%
4	613	3.9%
3	268	1.7%
2	207	1.3%
Other values (3)	61	0.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	9	0.1%
2	207	1.3%
3	268	1.7%
4	613	3.9%
5	1033	6.7%
6	2164	13.9%
7	3343	21.5%
8	838	5.4%
9	2143	13.8%
10	2909	18.7%

Value	Count	Frequency (%)
13	22	0.1%
12	30	0.2%
11	1953	12.6%
10	2909	18.7%
9	2143	13.8%
8	838	5.4%
7	3343	21.5%
6	2164	13.9%
5	1033	6.7%
4	613	3.9%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	df_index	Exposure	LicAge	RecordBeg	RecordEnd	Gender	MariStat	SocioCateg	VehUsage	DrivAge	HasKmLimit	BonusMalus	ClaimAmount	ClaimInd	Dataset	ClaimNbResp	ClaimNbNonResp	ClaimNbParking	ClaimNbWindscreen	OutUseNb	RiskArea
0	145813	0.62	11	2004-05-19	NaN	0	0	CSP6	Private	68	0	50	5377.20	1	5	1.00	0.00	1.00	1.00	0.00	4.00
1	145814	0.76	6	2004-01-01	2004-10-05	1	1	CSP5	Private+trip to office	47	0	50	2017.84	1	5	0.00	1.00	0.00	0.00	0.00	6.00
2	145833	0.02	5	2004-10-23	2004-11-01	0	0	CSP5	Private+trip to office	49	0	50	356.77	1	5	0.00	1.00	0.00	0.00	2.00	8.00
3	145845	0.83	10	2004-01-01	2004-11-01	0	0	CSP6	Private	75	0	50	645.13	1	5	0.00	0.00	0.00	0.00	0.00	9.00
4	145846	0.96	5	2004-01-01	2004-12-16	1	0	CSP5	Private+trip to office	49	0	54	1200.42	1	5	0.00	0.00	0.00	1.00	0.00	8.00
5	145850	0.61	10	2004-05-21	NaN	0	0	CSP6	Private	68	1	50	4326.53	1	5	0.00	0.00	0.00	0.00	0.00	10.00
6	145863	0.48	6	2004-01-01	2004-06-25	1	0	CSP1	Professional	48	0	64	2667.09	1	5	0.00	0.00	1.00	1.00	0.00	9.00
7	145866	1.00	5	2004-01-01	2004-12-31	0	0	CSP4	Professional	41	0	60	386.71	1	5	0.00	0.00	0.00	0.00	0.00	6.00
8	145883	0.10	8	2004-01-01	2004-02-06	0	1	CSP4	Professional	57	0	50	2020.64	1	5	0.00	1.00	0.00	0.00	0.00	11.00
9	145899	0.82	11	2004-03-07	NaN	0	0	CSP6	Private	71	0	50	467.73	1	5	0.00	0.00	1.00	0.00	0.00	7.00

Last rows

	df_index	Exposure	LicAge	RecordBeg	RecordEnd	Gender	SocioCateg	VehUsage	DrivAge	HasKmLimit	BonusMalus	ClaimAmount	ClaimInd	Dataset	ClaimNbResp	ClaimNbNonResp	ClaimNbParking	ClaimNbWindscreen	OutUseNb	RiskArea
15522	310862	0.51	8	2004-02-27	2004-09-01	1	CSP5	Private+trip to office	55	0	50	845.46	1	9	0.00	2.00	0.00	0.00	0.00	10.00
15523	310878	0.83	13	2004-03-01	NaN	0	CSP6	Private	75	0	50	351.32	1	9	0.00	0.00	0.00	0.00	1.00	7.00
15524	310880	0.92	4	2004-02-01	NaN	1	CSP5	Private+trip to office	37	0	64	776.04	1	9	0.00	0.00	0.00	1.00	2.00	7.00
15525	310884	1.00	8	2004-01-02	NaN	0	CSP5	Private+trip to office	55	0	50	2981.70	1	9	0.00	1.00	1.00	1.00	0.00	10.00
15526	310899	0.23	5	2004-04-02	2004-06-25	0	CSP4	Private+trip to office	49	0	50	277.19	1	9	1.00	0.00	0.00	1.00	2.00	10.00
15527	310910	0.33	9	2004-01-01	2004-05-01	0	CSP6	Private	70	1	50	230.74	1	9	0.00	1.00	0.00	0.00	0.00	9.00
15528	310963	0.18	7	2004-10-25	NaN	1	CSP5	Private	69	1	62	1562.36	1	9	2.00	0.00	0.00	0.00	0.00	7.00
15529	310967	0.75	9	2004-01-01	2004-10-01	0	CSP6	Private	63	0	50	476.32	1	9	0.00	1.00	0.00	1.00	0.00	6.00
15530	310973	0.42	6	2004-02-28	2004-07-30	0	CSP5	Private+trip to office	53	0	50	1117.89	1	9	0.00	0.00	0.00	0.00	0.00	7.00
15531	310976	1.00	7	2004-01-01	NaN	1	CSP5	Private+trip to office	54	0	50	2764.17	1	9	0.00	0.00	0.00	1.00	0.00	7.00

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block